Studi Perbandingan Teknik Thresholding Untuk Binarisasi Tanda Tangan Menggunakan OpenCV2: Metode Sederhana, Adaptif, Dan Otsu
Keywords:
Binarisasi Tanda Tangan, Thresholding, OpenCV2, Pengenalan Tanda TanganAbstract
The process of signature binarization is a crucial step in automatic signature recognition and verification. This research develops, implements, and evaluates three thresholding techniques—simple, adaptive, and Otsu—for signature binarization using the OpenCV2 library. Simple thresholding uses a single threshold for the entire image; adaptive thresholding adjusts the threshold based on different parts of the image; and the Otsu method determines the threshold automatically through histogram analysis. This study compares the effectiveness and reliability of these three techniques under various lighting conditions. The results indicate that simple thresholding is less effective in dark lighting conditions, while adaptive thresholding shows improved performance in handling lighting variations. The Otsu method provides the best results with its ability to automatically determine the optimal threshold, producing accurate and clear binary images.
References
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